1. Field of the Invention
The present invention generally relates to an electroencephalogram signal processing method and, more particularly, to an EEG signal processing method that preserves predetermined frequency band signals before removing interfering signals thereof.
2. Description of the Related Art
Electroencephalogram (EEG) data is a curved diagram formed by weak biological signals of a human brain, and is used to diagnose cerebrovascular diseases or epilepsy. However, EEG signals tend to be distorted under interferences caused by artifact sources. As an example, EEG signals are seriously interfered by eye movement, blink, muscle movement, electrocardiogram (EKG), power line noises, etc, leading to contamination of the EEG signals. In light of this, it is required to remove the interfering signals from the EEG signals before the EEG signals can be applied to medical diagnosis or brain status detection.
Conventionally, contaminated EEG signals are visually checked to find out interfering signals contained therein, and the interfering signals are removed from the EEG signals to complete the EEG signal processing method. Alternatively, U.S. Pat. No. 5,513,649 entitled “ADAPTIVE INTERFERENCE CANCELER FOR EEG MOVEMENT AND EYE ARTIFACTS” discloses a sensor that can detect and remove the interfering signals, which are caused by artifact sources, from EEG signals. The EEG signals without interfering signals are output as an output signal. Finally, a feedback operation is performed on the output signal to obtain needed EEG signals. However, when the EEG signals are in a small amount or seriously interfered by muscle movement or power line noises, removing the interfering signals from the contaminated EEG signals may lead to a loss of some useful information, making the processed EEG signals not useful for clinical diagnosis.
To solve the problem, other EEG signal processing methods were proposed to remove interfering signals from EEG signals based on Independent Component Analysis (ICA) algorithm. The ICA-based EEG signal processing methods can be seen in an IEEE paper entitled “Waveform-preserving blind estimation of multiple independent sources” or in a Taiwan patent with publication No. 201102047. In the Taiwan patent, independent components are retrieved from EEG data for blind signal separation (BSS). Namely, the independent components are retrieved for an ICA operation. Specifically, different interfering signals contained in the contaminated EEG data are separated as different ICA components. After the ICA components of the interfering signals are removed, other ICA components may construct a corrected EEG data, thereby removing the interfering signals from the EEG signals. However, since the signal sources in human brain are dependent from each other, the ICA components associated with interfering signals usually contain some frequency band signals required for certain EEG analysis, such as α waveforms (alpha rhythm) generated when human brain relaxes. As a result, the EEG data is not useful for clinical diagnosis.
In light of the above problems, it is desired to provide an EEG signal processing method capable of preserving the frequency band signals required for EEG analyses after removal of the interfering signals.